
In this paper, to alleviate the data bias problem, we propose the Posterior-and-Prior Knowledge Exploring-and-Distilling approach, which includes the Posterior and Prior Knowledge Explorer (PoKE and PrKE), and Multi-domain Knowledge Distiller (MKD).

The PoKE explores posterior knowledge by employing the disease topic tags to capture the rare, diverse and important abnormal regions; The PrKE explores prior knowledge from prior working experience and prior medical knowledge; The MKD distills the extracted knowledge to generate reports.

The experiments and analyses on the public IU-Xray and MIMIC-CXR datasets verify the effectiveness of our approach, which is able to outperform previous state-of-the-art model [1]} on these two datasets.

